Install dotcols

One self-contained bash binary. Bundles dot's runtime + dotcols's column types + Num/Sym/Data + the stats demo.

Requirements

Tool	Version	Why
`gawk`	≥ 4.x	indirect calls (`@fn`), `FUNCTAB`, `asorti`
`bash`	≥ 4.x	arrays, process substitution `<(...)`
`curl`	any	`--get-data` fetcher

Install

curl -sL https://raw.githubusercontent.com/timm/awk/master/dotcols/dotcols -o dotcols
chmod +x dotcols

Or install on PATH:

curl -sL https://raw.githubusercontent.com/timm/awk/master/dotcols/dotcols -o ~/.local/bin/dotcols
chmod +x ~/.local/bin/dotcols

Verify

One command. The bundled stats demo runs against its sample CSV (heart-disease, 14 columns):

./dotcols --demo stats | head -3

Expect:

column                      n          mid       spread
AGE                       303       54.366        9.082
sex                       303         male        0.624

Get example data

Pulls 30 curated CSVs (10 classification, 10 regression, 10 optimization) from the moot data repo into ./data/:

./dotcols --get-data

Layout:

data/classify/    iris wine glass heart.c diabetes breast.w ionosphere soybean zoo sonar
data/regression/  housing autompg auto93 abalone cpu.act bodyfat machine.cpu cal.housing fishcatch servo
data/optimize/    Apache_AllMeasurements HSMGP_num SQL_AllMeasurements rs-6d-c3_obj1 rs-6d-c3_obj2 sol-6d-c2-obj1 SS-A SS-B SS-C SS-D

Usage

dotcols FILE.awk [DATA...]    # run rewritten FILE.awk on DATA (or stdin)
dotcols a.awk b.awk DATA      # multi-file run; .awk args go through prep
cat DATA | dotcols FILE.awk   # stdin works too
dotcols -c FILE.awk           # print rewritten source only
dotcols --demo NAME [DATA]    # run demos/NAME/*.awk on DATA (or sample.*)
dotcols --demos               # list available demos under ./demos/
dotcols --show                # dump bundled lib/*.awk (post-prep)
dotcols --get-data            # fetch 30 curated CSVs into ./data/
dotcols --help                # full help

Try it on your data dirs

One command each. All three call --demo stats on a different CSV:

# classification: 4 numeric features + species class
dotcols --demo stats data/classify/iris.csv

# regression: Boston housing prices
dotcols --demo stats data/regression/housing.csv

# optimization: Apache web-server config tuning
dotcols --demo stats data/optimize/Apache_AllMeasurements.csv

Prefer git?

git clone https://github.com/timm/awk
cd awk/dotcols
./build.sh           # rebuild the dotcols binary from sources

The repo holds the modular sources (lib/numsym.awk, lib/data.awk) plus build.sh, which bundles them with ../dot/lib/* into the single-file dotcols binary.